opus-mt-en-ur Translation Model
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Developer | Helsinki-NLP |
| BLEU Score | 12.1 |
| chrF Score | 0.390 |
What is opus-mt-en-ur?
opus-mt-en-ur is a machine translation model developed by Helsinki-NLP specifically designed for English to Urdu translation. Built using the transformer-align architecture, this model represents part of the larger OPUS-MT project aimed at creating robust translation capabilities for diverse language pairs.
Implementation Details
The model employs a transformer-align architecture with SentencePiece tokenization (spm32k,spm32k) for both source and target languages. It underwent normalization preprocessing and was trained on the OPUS dataset, with the latest version released on June 17, 2020.
- Utilizes dual SentencePiece tokenization with 32k vocabulary
- Implements transformer-align architecture for enhanced translation quality
- Includes normalization preprocessing steps
- Achieves a BLEU score of 12.1 on the Tatoeba test set
Core Capabilities
- English to Urdu text translation
- Handles various text formats and lengths
- Supports batch processing
- Optimized for production deployment
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in English-to-Urdu translation using state-of-the-art transformer architecture with specific optimizations for this language pair. Its integration of SentencePiece tokenization and normalization preprocessing makes it particularly suitable for handling the complexities of Urdu script.
Q: What are the recommended use cases?
The model is best suited for general-purpose English to Urdu translation tasks, including document translation, content localization, and automated translation systems. With a BLEU score of 12.1, it's particularly useful for getting the gist of content, though human review is recommended for critical translations.
